2392 papers
Statistical mechanics explores how the chaotic motion of countless tiny particles gives rise to the predictable laws governing heat, pressure, and phase transitions. This field bridges the gap between the microscopic world of atoms and the macroscopic reality we experience daily, offering deep insights into why materials behave the way they do.
On Gist.Science, we process every new preprint in this category as it appears on arXiv to make these complex findings accessible to everyone. For each paper, we provide both a plain-language explanation for the curious reader and a detailed technical summary for specialists, ensuring that groundbreaking research is never lost behind a wall of jargon.
Below are the latest papers in statistical mechanics, freshly curated and summarized to help you understand the cutting edge of this fascinating discipline.
This paper introduces the quantum vector Hopfield network, demonstrating that intrinsic quantum fluctuations arising from non-commutative spin operators stabilize stored patterns and enhance both critical retrieval temperatures and pattern overlap compared to classical counterparts, thereby offering a new route to quantum-enhanced associative memory.
This paper demonstrates that the quantum Mpemba effect persists in strongly fragmented systems with charge and dipole conservation, manifesting as a higher-order phenomenon where asymmetries relax on distinct timescales through a mechanism involving frozen memory in inactive Krylov sectors and active relaxation in dynamic fragments.
This paper introduces a generative flow matching method that accurately captures non-Markovian and non-Gaussian effects in short-time stochastic particle dynamics, outperforming traditional regularized Dean-Kawasaki models in predicting statistical moments and first passage times.
This study demonstrates that the expansion dynamics of a strongly interacting Fermi gas in a shock tube geometry closely follow Riemann's inviscid Euler solution across a wide temperature range, with self-similarity persisting even on the BCS side despite significant increases in viscosity.
This paper demonstrates that applying a symmetry-breaking phase lag to a subset of oscillators in the second-order Kuramoto model with inertia can steer the primary cluster to merge with higher-order clusters, thereby overcoming the system's inherent tendency toward fragmented synchronization and enhancing global entrainment.
This study investigates how magnetic field, anisotropy, Dzyaloshinskii-Moriya interaction, and temperature modulate quantum resources in a two-qubit anisotropic XY model, revealing a distinct hierarchy of thermal degradation where nonlocality vanishes first while coherence persists longest, and demonstrating that anisotropy and DM interactions synergistically enhance the robustness of entanglement and correlations for spin-based quantum technologies.
This paper demonstrates that long-range interactions serve as a valuable resource for optimizing shortcuts to adiabaticity and enhancing quantum battery charging in open critical systems by enabling algebraically decaying control protocols and reducing operational costs compared to short-range interactions.
This paper decomposes the steady-state entropy production rate of Ornstein-Uhlenbeck processes into oscillatory and nonnormal contributions, revealing distinct fundamental trade-offs where the former strictly bounds dissipation against noise-induced oscillations and the latter links dissipation to the acceleration of relaxation.
This paper identifies and characterizes a novel class of topologically enforced Lifshitz multicritical points in one-dimensional chiral symmetric fermionic systems, which arise from changes in the topology of neighboring critical lines and exhibit robust topological degeneracies alongside a breakdown of the Li-Haldane bulk-boundary correspondence.
Using an analytically solvable noninteracting one-dimensional particle-on-a-ring model, this paper investigates how Lee-Yang zeros evolve with temperature to explain the failure of standard analytic continuation methods at low temperatures and proposes a novel fitting strategy that combines high-temperature extrapolation with temperature-dependent modeling to overcome the fermion sign problem.